The success of any organization depends on its vision and its ability to shape the future course of action with unmatched accuracy and timeliness. Wouldn’t it be great if this prediction part is made efficient, easy and streamlined for your employees which could ultimately lead to better fortunes!!

Predictive Analytics is one such technique that holds the potential to rise your business up-ahead from the market competition. Continue reading →

Machine Learning and Artificial Intelligence are considered as an integral part of the future technologies.

Artificial Intelligence is an area focused on developing intelligent machines that work and react like humans. To achieve this Artificial Intelligence considers all the traits that can help achieve the feat, these traits include perception, learning and planning. Machine learning on the other hand focuses on development of programs in such a way that systems can access data and use it to learn for themselves Artificial Intelligence focuses on making machines smart i.e. react as the situation demands whereas machine learning is based on providing machines access to data, making them learn themselves which makes their decisions learnt rather than smart.

Since you are reading this, I assume you are aware of, or at least have heard about Machine Learning and Artificial Intelligence. Being two of the hottest buzzwords in the industry right now, these are often used interchangeably leading to some confusion. However, these two have different meanings and applications. The two terms are very strongly related though, as they share a containership relationship between them where the former is a subset of the later. Lets dive deep into these topics and try to find the reason for this confusion and related solutions.

Why this confusion?

The main culprit behind this confusion is the interchangeable use of these two terms and the limited knowledge of the subject among the developer as well as user community. Artificial intelligence is heavily dependent on machine learning,

Machine Learning and AI confusion

which has led to the perception that both terms refer to the same thing. This confusion has spread like wildfire in the industry and only people who are experts in this field, know the clear distinction among these terms.

Artificial Intelligence-The Big Brother

Artificial Intelligence is the intelligence demonstrated by machines which emulates a human like thinking and behavior, allowing them to make their own decisions in real life situations. Going by the computer science definition, AI is referred to as the study of intelligent agents, which are devices that perceive their environment and take actions accordingly in order to maximum fulfillment of their goals. These agents mimic certain cognitive functions, which humans relate with the human mind, like problem solving and learning. AI, traditionally, attempts to solve problems such as Reasoning, Knowledge Representation, Learning, Planning, Natural Language Processing etc. Generating an intelligent agent which can think like humans is the long-term goal since it makes use of all the former techniques mentioned. Continue reading →

Salesforce released TransmogrifAI, a machine learning library written in Scala that runs on top of Spark. This can be potentially deployed on any cloud such as Heroku/PostgreSQL platform. What all is involved in TransmogrifAI?

Language: Scala

Underlying engine: Apache Spark data processing engine

Deployment platform: A standalone local machine or cloud platform like Heroku

Let us explore a bit more about these new players in the scene and whether they will align with our need to build robust machine learning models. The entry barrier to using the TransmogrifAI library is likely to be the new tech stack that a typical Salesforce developer needs to scale up to. Continue reading →

Start your journey to Salesforce DevOps with this infographic that captures introduction to different aspects of DevOps in Salesforce platform. It compares different approaches to Salesforce DevOps and finally has a deep-dive on Salesforce DX as well. Be it a free tool or a commercial one, do exercise caution while choosing any of the approaches – since it takes 6-12 months investment to stabilize a DevOps approach.

Salesforce DevOps InfoGraphic

Need help with Salesforce DevOps?

Call us at 855-Mirketa or write to us at info (at) mirketa.com to get FREE consultation on how to get started with Salesforce DevOps.

Salesforce DevOps is picking up steam with the recent focus on source driven development on Salesforce platform, particularly through increasing adoption of continuous integration and continuous delivery (CI/CD) using Salesforce DX. What contributed to this shift from ‘Changesets’ and ANT migration tool approaches? Following are some crucial factors: Continue reading →

People have always had an interest in what other people think, or what opinion they hold. Since the inception of the internet, increasing numbers of people are using websites and social media platform for expressing their opinion. Due to platforms such as Facebook, Twitter etc., it has become feasible to analyze and extract the public opinion on a certain topic, news story, product, or brand. Opinions that are mined from such services can be valuable. Data mined from these sources can be analyzed and presented accordingly to easily identify the online mood (positive, negative or neutral). This allows individuals or business to be proactive as opposed to reactive when a negative conversational thread is emerging. Alternatively, positive sentiments can be leveraged to identify product advocates as well to shape the business strategy by seeing the parts of the strategy that are working.

Technology has provided healthcare many breakthroughs in recent years and Salesforce has been at the forefront of that. So if this is the case why are most treatment centers still so far behind. Everyday people are scouring the internet trying to find a great place to recover from the diseases of Mental Health and Addiction. It’s estimated that over 20 million Americans over the age of 12 have an addiction. Many treatment centers lack the basic tools needed to be able to serve these patients with the care they need. As a consulting partner for Salesforce we have seen technology changing the face of Treatment Centers. Technology is providing treatment centers with the advanced tools needed to navigate the ever changing landscape. We’re going to outline 7 ways that technology is changing the face of treatment centers.

1. The addition of a CRM or Patient Relationship Management platform to the contact center is the number one way to better serving your patients. We have seen organizations taking notes on note pads or using excel to track patient calls. This is a major problem, in my experience working in a very busy Contact Center even your very best admissions representative will miss a follow up. Also in my experience, as a recovering alcoholic with almost 7 years of sobriety, I know that when I was ready to get help patience was not one of my strongest areas. So timely follow ups and the ability to take a call from beginning to end without hanging up the phone has resulted in a 35% increase in patient admissions based on case studies we have conducted.Continue reading →

Any business trying to grow and increase their client base needs a customer relationship management (CRM) software program. It’s just a simple fact that even the smallest businesses can’t avoid for very long before keeping track of clients starts to consume the entire day. Wineries are no exception.

The wine industry has a tendency to be reactive with their wine sales after they build a client relationship. The wine industry needs to have a CRM that empowers wineries to take action proactively in their marketing efforts. Salesforce has this ability through the use of marketing automation, data analytics, and AI. Salesforce can use your winery’s historical data of purchases made by clients to predict what products that client may be interested in. This allows wineries to target specific customers with specific content.

We hear a lot that wineries prefer to use a CRM or a software product that is specific to wineries. That’s a great option if you are just starting out, but you are missing out on a lot of value. It’s no secret that Salesforce’s success comes largely from its ability to be customized to each company’s specific requirements.

To put it plainly, Salesforce can be made into a customized winery CRM. The advantage that Salesforce brings to wineries is the support received from the business and marketing analytics. So, a winery will have the ability to do what we have come to expect from a CRM plus provide these strong tools that are designed to drive more sales through smarter marketing campaigns. Salesforce will feel like your winery CRM, not just a generic winery CRM. There are even winery specific apps available as add-ons to Salesforce. For example, GreatVines is a winery and beverage distributor sales app that helps sales teams manage client data in a more customized way to the beverage industry.